Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare

Wani, Niyaz Ahmad; Kumar, Ravinder; Mamta,; Bedi, Jatin; Rida, Imad

doi:10.1016/j.inffus.2024.102472

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Cited by 3 publications

References 195 publications

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Vision transformer based convolutional neural network for breast cancer histopathological images classification

ABIMOULOUD,

BENSID,

Elleuch

et al. 2024

Multimed Tools Appl

View full text Add to dashboard Cite

Vision transformer based convolutional neural network for breast cancer histopathological images classification

ABIMOULOUD,

BENSID,

Elleuch

et al. 2024

Multimed Tools Appl

View full text Add to dashboard Cite

Boost diagnostic performance in retinal disease classification utilizing deep ensemble classifiers based on OCT

Khan,

Khan

2024

Multimed Tools Appl

View full text Add to dashboard Cite

Explainable AI (XAI) for Green AI-Powered Disease Prognosis

Mittal,

Singh,

Gochhait

et al. 2024

Advances in Medical Diagnosis, Treatment, and Care

View full text Add to dashboard Cite

Accurate disease prognosis is crucial for improved healthcare outcomes. Artificial intelligence (AI) offers immense potential in this domain, but traditional “black-box” models lack interpretability. This chapter explores the integration of Explainable AI (XAI) with Green AI, a resource-efficient and sustainable approach to AI development. They discuss how XAI can enhance trust in Green AI models for disease prognosis, mitigate potential biases, and promote responsible AI development. They highlight the challenges of balancing interpretability with efficiency and propose future research directions to unlock the full potential of XAI for Green AI-powered disease prognosis. This approach has the potential to revolutionize healthcare by providing accurate, transparent, and environmentally friendly tools for early disease detection and improved patient outcomes.

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Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare

Cited by 3 publications

References 195 publications

Vision transformer based convolutional neural network for breast cancer histopathological images classification

Vision transformer based convolutional neural network for breast cancer histopathological images classification

Boost diagnostic performance in retinal disease classification utilizing deep ensemble classifiers based on OCT

Explainable AI (XAI) for Green AI-Powered Disease Prognosis

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